Overcoming Language Barrier for Scientific Studies via Unsupervised Literature Learning: Case Study on Solar Cell Materials Prediction

Data‐driven materials and chemical studies have been predominantly confined to English‐language databases, posing challenges for researchers in non‐English‐speaking regions to access and comprehend literature and derive scientific insights. Herein, a machine learning approach designed for informatio...

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Veröffentlicht in:	Solar RRL 2024-05, Vol.8 (10), p.n/a
Hauptverfasser:	Zhang, Lei, He, Mu, Huang, Endai, Ma, Xiaokang, You, Jiaxue, Jen, Alex Kwan Yue, Liu, Shengzhong (Frank)
Format:	Artikel
Sprache:	eng
Schlagworte:	data‐driven natural language processing oncologies solar cell materials unsupervised machine learning
Online-Zugang:	Volltext
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